-----------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\Pinotti\Dropbox\regulation\trustreg\data_Pinotti_RESTAT2012\results.log
  log type:  text
 opened on:  17 Aug 2012, 14:23:47

. use individual_level_data, clear

. 
. ********************************** INDIVIDUAL-LEVEL RESULTS **********************************
. 
. ****** TABLE 1 *******
. preserve

. gen observations=1

. collapse control trust pop2000 (sum) observations, by(codewb)

. replace pop2000=pop2000*1000
(32 real changes made)

. list codewb observations pop2000 control trust

     +--------------------------------------------------+
     | codewb   observ~s    pop2000   control     trust |
     |--------------------------------------------------|
  1. |    AUT       1366    8011560   4.09297    .34041 |
  2. |    BEL       1769   1.03e+07   5.60486    .29056 |
  3. |    BGR        875    8060000   5.34171   .269714 |
  4. |    BLR        832   1.00e+07   4.86899   .414663 |
  5. |    CZE       1823   1.03e+07   6.02304     .2452 |
     |--------------------------------------------------|
  6. |    DEU       1838   8.22e+07    4.9309   .380305 |
  7. |    DNK        905    5337344   4.41215   .678453 |
  8. |    ESP       1002   4.03e+07   5.42415   .381238 |
  9. |    EST        893    1369512   6.06495   .235162 |
 10. |    FIN        942    5176197    4.6242   .570064 |
     |--------------------------------------------------|
 11. |    FRA       1519   5.89e+07   4.89928   .210665 |
 12. |    GBR       1717   5.97e+07    4.6855    .34537 |
 13. |    GRC        948   1.09e+07    5.7173   .238397 |
 14. |    HRV        940    4502500   5.04681   .203191 |
 15. |    HUN        910   1.02e+07   6.63297   .228571 |
     |--------------------------------------------------|
 16. |    IRL        923    3805400   4.98267   .368364 |
 17. |    ISL        900     281000   3.36222   .413333 |
 18. |    ITA       1845   5.69e+07   4.91491   .334959 |
 19. |    LTU        884    3499527   4.49774   .260181 |
 20. |    LUX       1038     438000   6.44605   .250482 |
     |--------------------------------------------------|
 21. |    LVA        942    2372000   7.36518   .169851 |
 22. |    MLT        980     390000    4.9949   .208163 |
 23. |    NLD        978   1.59e+07   5.43763   .600205 |
 24. |    POL       1007   3.85e+07   6.73088     .1857 |
 25. |    PRT        883   1.02e+07   5.49151   .132503 |
     |--------------------------------------------------|
 26. |    ROM       1032   2.24e+07   6.21705   .101744 |
 27. |    RUS       2265   1.46e+08    6.1638   .243267 |
 28. |    SVK       1218    5388740   7.13793   .157635 |
 29. |    SVN        926    1989000   5.54536   .214903 |
 30. |    SWE        948    8869000   3.90084   .667722 |
     |--------------------------------------------------|
 31. |    TUR       1107   6.74e+07   6.91057   .066847 |
 32. |    UKR       1067   4.92e+07   5.45736   .268978 |
     +--------------------------------------------------+

. restore

. 
. ****** TABLE 2 *******
. ologit control trust [pw=weight], robust 

Iteration 0:   log pseudolikelihood =   -1709187  
Iteration 1:   log pseudolikelihood = -1706048.9  
Iteration 2:   log pseudolikelihood = -1706047.8  
Iteration 3:   log pseudolikelihood = -1706047.8  

Ordered logistic regression                       Number of obs   =      37222
                                                  Wald chi2(1)    =     158.73
                                                  Prob > chi2     =     0.0000
Log pseudolikelihood = -1706047.8                 Pseudo R2       =     0.0018

------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.3491389   .0277119   -12.60   0.000    -.4034532   -.2948246
-------------+----------------------------------------------------------------
       /cut1 |  -2.082406   .0265626                     -2.134467   -2.030344
       /cut2 |  -1.527264   .0228365                     -1.572022   -1.482505
       /cut3 |  -1.010972   .0203907                     -1.050937   -.9710066
       /cut4 |  -.6308121   .0193213                     -.6686811   -.5929431
       /cut5 |   .0638409   .0185454                      .0274925    .1001892
       /cut6 |   .3676413    .018769                      .3308548    .4044278
       /cut7 |   .7015012   .0193802                      .6635167    .7394858
       /cut8 |   1.217447   .0212617                      1.175775    1.259119
       /cut9 |   1.675845   .0239315                       1.62894     1.72275
------------------------------------------------------------------------------

. xi: ologit control trust i.codewb [pw=weight], robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

Iteration 0:   log pseudolikelihood =   -1709187  
Iteration 1:   log pseudolikelihood = -1679050.6  
Iteration 2:   log pseudolikelihood = -1678898.7  
Iteration 3:   log pseudolikelihood = -1678898.6  

Ordered logistic regression                       Number of obs   =      37222
                                                  Wald chi2(0)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -1678898.6                 Pseudo R2       =     0.0177

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1646903   .0459934    -3.58   0.000    -.2548358   -.0745449
  _Icodewb_2 |    .960275    .059295    16.19   0.000     .8440589    1.076491
  _Icodewb_3 |   .7666289    .048036    15.96   0.000     .6724801    .8607777
  _Icodewb_4 |   .4498232    .022196    20.27   0.000     .4063198    .4933266
  _Icodewb_5 |   1.150326   .0695121    16.55   0.000     1.014085    1.286568
  _Icodewb_6 |   .3440355    .019474    17.67   0.000     .3058672    .3822037
  _Icodewb_7 |   .3117934   .0206994    15.06   0.000     .2712232    .3523636
  _Icodewb_8 |    .838176   .0490984    17.07   0.000      .741945     .934407
  _Icodewb_9 |   1.200309   .0750886    15.99   0.000     1.053139     1.34748
 _Icodewb_10 |   .4313087   .0247138    17.45   0.000     .3828706    .4797468
 _Icodewb_11 |   .4613371   .0297606    15.50   0.000     .4030073    .5196669
 _Icodewb_12 |   .4114853   .0254636    16.16   0.000     .3615774    .4613931
 _Icodewb_13 |   .9700418   .0596326    16.27   0.000     .8531642     1.08692
 _Icodewb_14 |   .7562238   .0487266    15.52   0.000     .6607213    .8517262
 _Icodewb_15 |   1.553682   .0876257    17.73   0.000     1.381939    1.725426
 _Icodewb_16 |   .6040161   .0368333    16.40   0.000     .5318242     .676208
 _Icodewb_17 |  -.3641933   .0190697   -19.10   0.000    -.4015693   -.3268173
 _Icodewb_18 |   .5067144   .0305525    16.59   0.000     .4468325    .5665962
 _Icodewb_19 |   .2892361   .0165933    17.43   0.000     .2567139    .3217584
 _Icodewb_20 |   1.391733   .0800499    17.39   0.000     1.234838    1.548628
 _Icodewb_21 |   1.984355   .1102439    18.00   0.000     1.768281    2.200429
 _Icodewb_22 |   .5373092   .0340623    15.77   0.000     .4705484      .60407
 _Icodewb_23 |   .9075308   .0548912    16.53   0.000     .7999461    1.015116
 _Icodewb_24 |   1.578085    .089963    17.54   0.000     1.401761    1.754409
 _Icodewb_25 |    .880048   .0563001    15.63   0.000     .7697019    .9903941
 _Icodewb_26 |   1.334358   .0845039    15.79   0.000     1.168734    1.499983
 _Icodewb_27 |   1.204646   .0713202    16.89   0.000     1.064861    1.344431
 _Icodewb_28 |   1.802765   .1033455    17.44   0.000     1.600211    2.005318
 _Icodewb_29 |   .8592694   .0498536    17.24   0.000     .7615581    .9569807
 _Icodewb_30 |   .0506199   .0149834     3.38   0.001      .021253    .0799867
 _Icodewb_31 |   1.803002   .1034196    17.43   0.000     1.600303    2.005701
 _Icodewb_32 |   .7823653   .0448238    17.45   0.000     .6945123    .8702183
-------------+----------------------------------------------------------------
       /cut1 |  -1.234152   .0864332                     -1.403558   -1.064746
       /cut2 |  -.6726058   .0468317                     -.7643942   -.5808174
       /cut3 |   -.142364   .0231905                     -.1878165   -.0969114
       /cut4 |   .2539295   .0418842                       .171838    .3360211
       /cut5 |   .9855123   .0621811                      .8636396    1.107385
       /cut6 |   1.307342   .0878571                      1.135145    1.479539
       /cut7 |   1.662998   .1184409                      1.430858    1.895138
       /cut8 |   2.212577   .1441676                      1.930013     2.49514
       /cut9 |   2.695615   .1496667                      2.402273    2.988956
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb [pw=weight], robus
> t cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood = -1461044.7  
Iteration 1:   log pseudolikelihood = -1426303.3  
Iteration 2:   log pseudolikelihood = -1426085.4  
Iteration 3:   log pseudolikelihood = -1426085.4  

Ordered logistic regression                       Number of obs   =      31489
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -1426085.4                 Pseudo R2       =     0.0239

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1297142   .0446037    -2.91   0.004    -.2171357   -.0422926
         age |   1.910908   .8260016     2.31   0.021     .2919749    3.529842
        age2 |  -1.337888   .9817683    -1.36   0.173    -3.262118    .5863428
      female |   .1887586   .0349517     5.40   0.000     .1202545    .2572627
  highincome |  -.2972178   .0336097    -8.84   0.000    -.3630916    -.231344
   lowincome |   .0591552    .057337     1.03   0.302    -.0532232    .1715336
  highschool |  -.2060045   .0503547    -4.09   0.000    -.3046979    -.107311
   lowschool |   .1238436   .0446284     2.77   0.006     .0363736    .2113136
      female |          0  (omitted)
  _Icodewb_2 |   1.047204   .0564088    18.56   0.000     .9366445    1.157763
  _Icodewb_3 |   .8362798   .0502468    16.64   0.000      .737798    .9347616
  _Icodewb_4 |   .4158174   .0207656    20.02   0.000     .3751176    .4565171
  _Icodewb_5 |   1.088481   .0616981    17.64   0.000     .9675545    1.209407
  _Icodewb_6 |   .1984326   .0223106     8.89   0.000     .1547048    .2421605
  _Icodewb_7 |   .2998033   .0156908    19.11   0.000     .2690498    .3305568
  _Icodewb_8 |    .790373   .0484795    16.30   0.000     .6953549    .8853912
  _Icodewb_9 |   1.263315   .0725049    17.42   0.000     1.121208    1.405422
 _Icodewb_10 |   .4143461   .0191403    21.65   0.000     .3768318    .4518603
 _Icodewb_11 |   .4742517   .0259624    18.27   0.000     .4233663    .5251371
 _Icodewb_12 |   .4165955   .0241619    17.24   0.000     .3692389     .463952
 _Icodewb_13 |    1.10024   .0451772    24.35   0.000     1.011695    1.188786
 _Icodewb_14 |   .7756094   .0387146    20.03   0.000     .6997302    .8514885
 _Icodewb_15 |   1.517618   .0776807    19.54   0.000     1.365367     1.66987
 _Icodewb_16 |   .6452924   .0275265    23.44   0.000     .5913415    .6992434
 _Icodewb_17 |  -.3458117   .0324515   -10.66   0.000    -.4094155   -.2822078
 _Icodewb_18 |   .4750679   .0223319    21.27   0.000     .4312983    .5188376
 _Icodewb_19 |   .3889498   .0195763    19.87   0.000      .350581    .4273187
 _Icodewb_20 |   1.438698   .0708872    20.30   0.000     1.299762    1.577634
 _Icodewb_21 |   1.952742   .0993311    19.66   0.000     1.758056    2.147427
 _Icodewb_22 |   .5432664   .0357968    15.18   0.000      .473106    .6134268
 _Icodewb_23 |   .9099827   .0416282    21.86   0.000      .828393    .9915724
 _Icodewb_24 |   1.487886   .0765211    19.44   0.000     1.337908    1.637865
 _Icodewb_25 |   .8139828   .0538191    15.12   0.000     .7084994    .9194663
 _Icodewb_26 |    1.34948   .0747606    18.05   0.000     1.202952    1.496008
 _Icodewb_27 |   1.272315   .0635449    20.02   0.000     1.147769     1.39686
 _Icodewb_28 |   1.854565   .0945199    19.62   0.000     1.669309    2.039821
 _Icodewb_29 |   .9229713   .0455681    20.25   0.000     .8336595    1.012283
 _Icodewb_30 |   .0798051     .02069     3.86   0.000     .0392533    .1203568
 _Icodewb_31 |   1.815404   .0855612    21.22   0.000     1.647707    1.983101
 _Icodewb_32 |   .8352336   .0400142    20.87   0.000     .7568072      .91366
-------------+----------------------------------------------------------------
       /cut1 |  -.6565177    .218862                     -1.085479   -.2275561
       /cut2 |  -.0849497   .1980877                     -.4731944    .3032951
       /cut3 |   .4412689   .2034988                      .0424186    .8401192
       /cut4 |   .8378418   .2107395                      .4247998    1.250884
       /cut5 |   1.550903   .2319844                      1.096222    2.005584
       /cut6 |   1.874609   .2449438                      1.394528     2.35469
       /cut7 |   2.226516   .2689599                      1.699364    2.753668
       /cut8 |   2.784657   .2945842                      2.207283    3.362032
       /cut9 |   3.277169   .2944057                      2.700144    3.854193
------------------------------------------------------------------------------

. xi: ologit control trust insider age age2 female highincome lowincome highschool lowschool female i.codewb [pw=weight
> ], robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood = -1458029.6  
Iteration 1:   log pseudolikelihood = -1422506.2  
Iteration 2:   log pseudolikelihood = -1422275.5  
Iteration 3:   log pseudolikelihood = -1422275.4  

Ordered logistic regression                       Number of obs   =      31383
                                                  Wald chi2(8)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -1422275.4                 Pseudo R2       =     0.0245

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1249667   .0437413    -2.86   0.004    -.2106979   -.0392354
     insider |  -.3481296   .1062043    -3.28   0.001    -.5562861   -.1399731
         age |   2.212962   .8344761     2.65   0.008     .5774187    3.848505
        age2 |  -1.618222   1.010246    -1.60   0.109    -3.598267    .3618236
      female |   .1600899   .0377551     4.24   0.000     .0860912    .2340886
  highincome |  -.2799362   .0350075    -8.00   0.000    -.3485496   -.2113227
   lowincome |    .060096   .0553804     1.09   0.278    -.0484475    .1686396
  highschool |  -.1914762    .051345    -3.73   0.000    -.2921106   -.0908418
   lowschool |   .1206228   .0432294     2.79   0.005     .0358948    .2053508
      female |          0  (omitted)
  _Icodewb_2 |   1.079663   .0602001    17.93   0.000     .9616726    1.197653
  _Icodewb_3 |   .8350633    .049837    16.76   0.000     .7373846    .9327419
  _Icodewb_4 |   .4169668   .0208703    19.98   0.000     .3760619    .4578718
  _Icodewb_5 |   1.093145    .062263    17.56   0.000     .9711114    1.215178
  _Icodewb_6 |   .1966125   .0215776     9.11   0.000     .1543213    .2389037
  _Icodewb_7 |   .3131374   .0173316    18.07   0.000     .2791682    .3471067
  _Icodewb_8 |   .7958906   .0492914    16.15   0.000     .6992813    .8924999
  _Icodewb_9 |   1.272544    .073299    17.36   0.000     1.128881    1.416207
 _Icodewb_10 |   .4260793   .0225754    18.87   0.000     .3818323    .4703262
 _Icodewb_11 |   .4694107   .0260533    18.02   0.000     .4183471    .5204742
 _Icodewb_12 |    .430253   .0254079    16.93   0.000     .3804545    .4800516
 _Icodewb_13 |   1.112427    .042858    25.96   0.000     1.028426    1.196427
 _Icodewb_14 |   .7613038   .0377736    20.15   0.000      .687269    .8353386
 _Icodewb_15 |   1.515148   .0774243    19.57   0.000     1.363399    1.666897
 _Icodewb_16 |   .6753502   .0311939    21.65   0.000     .6142112    .7364892
 _Icodewb_17 |  -.3051989    .026775   -11.40   0.000    -.3576769   -.2527208
 _Icodewb_18 |   .5034308   .0266986    18.86   0.000     .4511024    .5557592
 _Icodewb_19 |   .3751137   .0180456    20.79   0.000     .3397451    .4104824
 _Icodewb_20 |   1.421998   .0694185    20.48   0.000     1.285941    1.558056
 _Icodewb_21 |   1.947387    .098898    19.69   0.000     1.753551    2.141224
 _Icodewb_22 |   .5496133   .0364313    15.09   0.000     .4782092    .6210173
 _Icodewb_23 |   .9192277   .0432976    21.23   0.000     .8343659    1.004089
 _Icodewb_24 |   1.489759   .0769719    19.35   0.000     1.338897    1.640621
 _Icodewb_25 |   .8276507   .0556267    14.88   0.000     .7186243    .9366771
 _Icodewb_26 |   1.328377   .0730849    18.18   0.000     1.185133    1.471621
 _Icodewb_27 |   1.271773   .0629833    20.19   0.000     1.148328    1.395218
 _Icodewb_28 |   1.855696   .0943143    19.68   0.000     1.670843    2.040548
 _Icodewb_29 |   .9132583   .0445884    20.48   0.000     .8258666     1.00065
 _Icodewb_30 |   .0516299   .0231249     2.23   0.026     .0063059    .0969539
 _Icodewb_31 |   1.848663   .0869003    21.27   0.000     1.678342    2.018985
 _Icodewb_32 |   .8378743   .0397356    21.09   0.000      .759994    .9157546
-------------+----------------------------------------------------------------
       /cut1 |  -.6223516   .2164481                     -1.046582   -.1981211
       /cut2 |  -.0486968   .1960203                     -.4328895    .3354959
       /cut3 |    .477474   .2019812                      .0815982    .8733498
       /cut4 |   .8756069   .2096691                      .4646629    1.286551
       /cut5 |   1.589773   .2317023                      1.135645    2.043901
       /cut6 |   1.914329   .2450805                       1.43398    2.394678
       /cut7 |   2.266621   .2693181                      1.738767    2.794475
       /cut8 |   2.824972   .2948048                      2.247166    3.402779
       /cut9 |   3.317244   .2948561                      2.739337    3.895152
------------------------------------------------------------------------------

. xi: ologit control trust burpol incumbent age age2 female highincome lowincome highschool lowschool female i.codewb [
> pw=weight], robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
note: _Icodewb_30 omitted because of collinearity
note: _Icodewb_31 omitted because of collinearity
Iteration 0:   log pseudolikelihood = -993498.13  
Iteration 1:   log pseudolikelihood = -969668.92  
Iteration 2:   log pseudolikelihood = -969521.43  
Iteration 3:   log pseudolikelihood = -969521.38  

Ordered logistic regression                       Number of obs   =      22901
                                                  Wald chi2(9)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -969521.38                 Pseudo R2       =     0.0241

                                (Std. Err. adjusted for 30 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1388204   .0458886    -3.03   0.002    -.2287605   -.0488803
      burpol |    .267277   .2763302     0.97   0.333    -.2743203    .8088744
   incumbent |   -.421247   .1266098    -3.33   0.001    -.6693975   -.1730964
         age |   2.995006   .7129779     4.20   0.000     1.597595    4.392417
        age2 |  -2.302327   .9944501    -2.32   0.021    -4.251413   -.3532403
      female |   .2091552   .0428506     4.88   0.000     .1251695    .2931409
  highincome |  -.2230271   .0637485    -3.50   0.000     -.347972   -.0980823
   lowincome |   .0825977   .0800723     1.03   0.302    -.0743411    .2395364
  highschool |  -.1768001    .054605    -3.24   0.001    -.2838239   -.0697763
   lowschool |   .1982834   .0244215     8.12   0.000     .1504181    .2461488
      female |          0  (omitted)
  _Icodewb_2 |   1.154571   .0511478    22.57   0.000     1.054323    1.254819
  _Icodewb_3 |   .8552958   .0565148    15.13   0.000     .7445288    .9660628
  _Icodewb_4 |   .4898653   .0206326    23.74   0.000     .4494261    .5303046
  _Icodewb_5 |   1.106165   .0660163    16.76   0.000     .9767759    1.235555
  _Icodewb_6 |   .1793786   .0345882     5.19   0.000     .1115869    .2471702
  _Icodewb_7 |   .3149169   .0271733    11.59   0.000     .2616582    .3681756
  _Icodewb_8 |   .9123443   .0523866    17.42   0.000     .8096684     1.01502
  _Icodewb_9 |   1.329087   .0705796    18.83   0.000     1.190753     1.46742
 _Icodewb_10 |   .4318303   .0369085    11.70   0.000      .359491    .5041695
 _Icodewb_11 |   .4688319   .0318735    14.71   0.000     .4063609    .5313028
 _Icodewb_12 |   .4659545   .0316114    14.74   0.000     .4039972    .5279117
 _Icodewb_13 |   1.113174   .0260128    42.79   0.000      1.06219    1.164158
 _Icodewb_14 |   .8029449   .0270996    29.63   0.000     .7498307     .856059
 _Icodewb_15 |   1.576607   .0726921    21.69   0.000     1.434133    1.719081
 _Icodewb_16 |   .7887556   .0261439    30.17   0.000     .7375144    .8399968
 _Icodewb_17 |  -.2878409     .03135    -9.18   0.000    -.3492857   -.2263961
 _Icodewb_18 |   .5653598   .0309691    18.26   0.000     .5046614    .6260582
 _Icodewb_19 |   .4804625   .0136087    35.31   0.000       .45379    .5071349
 _Icodewb_20 |   1.394995   .0383699    36.36   0.000     1.319791    1.470198
 _Icodewb_21 |   2.064485   .0975848    21.16   0.000     1.873223    2.255748
 _Icodewb_22 |   .6339825   .0313092    20.25   0.000     .5726176    .6953474
 _Icodewb_23 |   1.030534   .0284985    36.16   0.000     .9746783     1.08639
 _Icodewb_24 |   1.577687   .0792552    19.91   0.000      1.42235    1.733024
 _Icodewb_25 |   .8597694   .0563269    15.26   0.000     .7493707    .9701681
 _Icodewb_26 |   1.252143   .0561333    22.31   0.000     1.142124    1.362162
 _Icodewb_27 |   1.396655   .0575918    24.25   0.000     1.283777    1.509533
 _Icodewb_28 |   1.891035   .0816624    23.16   0.000     1.730979     2.05109
 _Icodewb_29 |   .9980822   .0419895    23.77   0.000     .9157842     1.08038
 _Icodewb_30 |          0  (omitted)
 _Icodewb_31 |          0  (omitted)
 _Icodewb_32 |    .949266    .044728    21.22   0.000     .8616007    1.036931
-------------+----------------------------------------------------------------
       /cut1 |  -.3321558    .176589                     -.6782638    .0139523
       /cut2 |   .2323483   .1598611                     -.0809736    .5456703
       /cut3 |   .7736129   .1560338                      .4677923    1.079434
       /cut4 |     1.1681   .1584585                      .8575273    1.478673
       /cut5 |   1.910002   .1434269                       1.62889    2.191113
       /cut6 |   2.234961   .1446535                      1.951445    2.518476
       /cut7 |   2.614689   .1484833                      2.323667    2.905711
       /cut8 |   3.189832   .1655863                      2.865289    3.514375
       /cut9 |   3.672718   .1554626                      3.368017    3.977419
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb [pw=weight] if ins
> ider==0, robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood = -1318843.2  
Iteration 1:   log pseudolikelihood = -1287900.9  
Iteration 2:   log pseudolikelihood =   -1287706  
Iteration 3:   log pseudolikelihood = -1287705.9  

Ordered logistic regression                       Number of obs   =      28370
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -1287705.9                 Pseudo R2       =     0.0236

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1317571   .0429133    -3.07   0.002    -.2158655   -.0476486
         age |   2.585718   .7968602     3.24   0.001     1.023901    4.147536
        age2 |  -1.994425   .9507921    -2.10   0.036    -3.857943   -.1309063
      female |   .1433938   .0374062     3.83   0.000      .070079    .2167085
  highincome |  -.2707372   .0348103    -7.78   0.000    -.3389641   -.2025103
   lowincome |   .0490872   .0553639     0.89   0.375    -.0594242    .1575985
  highschool |  -.2458852   .0472435    -5.20   0.000    -.3384807   -.1532897
   lowschool |   .1129598   .0406565     2.78   0.005     .0332746     .192645
      female |          0  (omitted)
  _Icodewb_2 |   1.131834   .0586049    19.31   0.000     1.016971    1.246698
  _Icodewb_3 |   .8698862   .0527946    16.48   0.000     .7664108    .9733617
  _Icodewb_4 |   .4237694   .0208106    20.36   0.000     .3829813    .4645575
  _Icodewb_5 |   1.124415   .0642699    17.50   0.000     .9984484    1.250382
  _Icodewb_6 |   .1588409   .0212536     7.47   0.000     .1171846    .2004971
  _Icodewb_7 |      .3403   .0159159    21.38   0.000     .3091053    .3714947
  _Icodewb_8 |    .781997   .0489481    15.98   0.000     .6860604    .8779335
  _Icodewb_9 |   1.279967    .074165    17.26   0.000     1.134606    1.425328
 _Icodewb_10 |   .4364576   .0228661    19.09   0.000     .3916408    .4812744
 _Icodewb_11 |    .493393   .0276587    17.84   0.000     .4391828    .5476031
 _Icodewb_12 |   .4181717   .0268158    15.59   0.000     .3656136    .4707297
 _Icodewb_13 |   1.141249   .0399881    28.54   0.000     1.062874    1.219624
 _Icodewb_14 |   .7685875   .0370595    20.74   0.000     .6959523    .8412228
 _Icodewb_15 |   1.531268   .0800409    19.13   0.000     1.374391    1.688146
 _Icodewb_16 |    .607161   .0289266    20.99   0.000     .5504659    .6638561
 _Icodewb_17 |  -.3651345   .0331601   -11.01   0.000    -.4301272   -.3001418
 _Icodewb_18 |   .5251246   .0256712    20.46   0.000     .4748099    .5754392
 _Icodewb_19 |   .3234428   .0142238    22.74   0.000     .2955646    .3513209
 _Icodewb_20 |   1.420757   .0682408    20.82   0.000     1.287007    1.554506
 _Icodewb_21 |   1.959432   .0950985    20.60   0.000     1.773042    2.145821
 _Icodewb_22 |   .5206944   .0342655    15.20   0.000     .4535353    .5878535
 _Icodewb_23 |   .8931789   .0441486    20.23   0.000     .8066493    .9797085
 _Icodewb_24 |   1.506712   .0761299    19.79   0.000       1.3575    1.655924
 _Icodewb_25 |   .7431005   .0541288    13.73   0.000       .63701     .849191
 _Icodewb_26 |   1.351348   .0718433    18.81   0.000     1.210538    1.492158
 _Icodewb_27 |   1.234769   .0585585    21.09   0.000     1.119996    1.349541
 _Icodewb_28 |   1.869087   .0911717    20.50   0.000     1.690394     2.04778
 _Icodewb_29 |   .9196597   .0434926    21.15   0.000     .8344158    1.004904
 _Icodewb_30 |   .0487744   .0225365     2.16   0.030     .0046037    .0929452
 _Icodewb_31 |   1.840708   .0807097    22.81   0.000      1.68252    1.998896
 _Icodewb_32 |   .8623032    .038414    22.45   0.000     .7870131    .9375933
-------------+----------------------------------------------------------------
       /cut1 |  -.5960323   .2130073                     -1.013519   -.1785456
       /cut2 |  -.0201454   .1885165                     -.3896308    .3493401
       /cut3 |   .5056138   .1884714                      .1362167    .8750109
       /cut4 |   .9127383   .1936713                      .5331496    1.292327
       /cut5 |    1.63843   .2178858                      1.211382    2.065479
       /cut6 |   1.968612   .2295634                      1.518676    2.418548
       /cut7 |   2.324488   .2526396                      1.829323    2.819652
       /cut8 |   2.893271   .2759177                      2.352482     3.43406
       /cut9 |   3.400233    .272966                      2.865229    3.935237
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb [pw=weight] if ins
> ider==1, robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood = -136944.05  
Iteration 1:   log pseudolikelihood = -132361.92  
Iteration 2:   log pseudolikelihood = -132323.02  
Iteration 3:   log pseudolikelihood = -132322.99  
Iteration 4:   log pseudolikelihood = -132322.99  

Ordered logistic regression                       Number of obs   =       3013
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -132322.99                 Pseudo R2       =     0.0337

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.0632374   .1003729    -0.63   0.529    -.2599646    .1334899
         age |   -2.33956   2.141147    -1.09   0.275    -6.536131     1.85701
        age2 |   2.881298    2.33116     1.24   0.216    -1.687691    7.450287
      female |    .395464   .0993231     3.98   0.000     .2007943    .5901337
  highincome |  -.3491853   .1457972    -2.40   0.017    -.6349425   -.0634281
   lowincome |   .2467634   .1246285     1.98   0.048      .002496    .4910307
  highschool |   .1761368   .1403667     1.25   0.210    -.0989769    .4512505
   lowschool |   .1832847   .2368776     0.77   0.439    -.2809869    .6475562
      female |          0  (omitted)
  _Icodewb_2 |   .8091774   .0477075    16.96   0.000     .7156725    .9026824
  _Icodewb_3 |   .5814081    .061254     9.49   0.000     .4613524    .7014638
  _Icodewb_4 |   .2878979   .0846461     3.40   0.001     .1219945    .4538012
  _Icodewb_5 |   .8275278   .0561522    14.74   0.000     .7174715     .937584
  _Icodewb_6 |   .6779932   .0374235    18.12   0.000     .6046445    .7513418
  _Icodewb_7 |   .2273642   .0469069     4.85   0.000     .1354285       .3193
  _Icodewb_8 |   1.025529   .0543163    18.88   0.000     .9190708    1.131987
  _Icodewb_9 |   1.247419   .0915396    13.63   0.000     1.068004    1.426833
 _Icodewb_10 |   .4936828   .0406559    12.14   0.000     .4139987     .573367
 _Icodewb_11 |   .1394292   .0384884     3.62   0.000     .0639934    .2148651
 _Icodewb_12 |   .6029962   .0402986    14.96   0.000     .5240124    .6819801
 _Icodewb_13 |   .9756637   .0944054    10.33   0.000     .7906326    1.160695
 _Icodewb_14 |   .5419609   .0583306     9.29   0.000     .4276351    .6562867
 _Icodewb_15 |   1.318165   .0767121    17.18   0.000     1.167812    1.468518
 _Icodewb_16 |    1.18458   .0735856    16.10   0.000     1.040355    1.328805
 _Icodewb_17 |   .0344267   .0318288     1.08   0.279    -.0279566      .09681
 _Icodewb_18 |   .4613267   .0442714    10.42   0.000     .3745563    .5480971
 _Icodewb_19 |   1.168618   .1127711    10.36   0.000     .9475909    1.389646
 _Icodewb_20 |   1.408922   .0899737    15.66   0.000     1.232577    1.585267
 _Icodewb_21 |   1.861529   .1346427    13.83   0.000     1.597634    2.125424
 _Icodewb_22 |    .933066   .0737551    12.65   0.000     .7885087    1.077623
 _Icodewb_23 |   1.159827   .0713039    16.27   0.000     1.020074     1.29958
 _Icodewb_24 |   1.286839   .0951614    13.52   0.000     1.100326    1.473352
 _Icodewb_25 |   1.566893   .1487182    10.54   0.000     1.275411    1.858376
 _Icodewb_26 |   .7187228   .1030378     6.98   0.000     .5167724    .9206733
 _Icodewb_27 |   1.698146   .1041608    16.30   0.000     1.493994    1.902297
 _Icodewb_28 |   1.764704   .1227317    14.38   0.000     1.524154    2.005254
 _Icodewb_29 |   .7461595   .0660959    11.29   0.000      .616614     .875705
 _Icodewb_30 |  -.1996919   .0464294    -4.30   0.000    -.2906919   -.1086918
 _Icodewb_31 |   1.932453    .210221     9.19   0.000     1.520427    2.344478
 _Icodewb_32 |   .6303611   .0563253    11.19   0.000     .5199655    .7407567
-------------+----------------------------------------------------------------
       /cut1 |  -.8924313   .5871423                     -2.043209    .2583465
       /cut2 |  -.3105723   .5726553                     -1.432956    .8118115
       /cut3 |   .2419403   .5832251                     -.9011599     1.38504
       /cut4 |    .579496   .5751983                     -.5478719    1.706864
       /cut5 |   1.206403   .6013379                      .0278028    2.385004
       /cut6 |   1.480679   .6144388                      .2764005    2.684957
       /cut7 |   1.801959   .6420137                       .543635    3.060283
       /cut8 |   2.259018   .6736034                      .9387794    3.579256
       /cut9 |   2.612571   .6636681                      1.311805    3.913337
------------------------------------------------------------------------------

. 
. * additional results: no weighting
. ologit control trust, robust 

Iteration 0:   log pseudolikelihood = -84082.701  
Iteration 1:   log pseudolikelihood = -83849.109  
Iteration 2:   log pseudolikelihood = -83848.974  
Iteration 3:   log pseudolikelihood = -83848.974  

Ordered logistic regression                       Number of obs   =      37222
                                                  Wald chi2(1)    =     519.51
                                                  Prob > chi2     =     0.0000
Log pseudolikelihood = -83848.974                 Pseudo R2       =     0.0028

------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.4209993   .0184707   -22.79   0.000    -.4572012   -.3847973
-------------+----------------------------------------------------------------
       /cut1 |  -2.132417   .0181715                     -2.168032   -2.096801
       /cut2 |  -1.543954   .0153752                     -1.574089   -1.513819
       /cut3 |  -1.009505   .0136649                     -1.036288   -.9827226
       /cut4 |   -.634999   .0129165                     -.6603149   -.6096832
       /cut5 |   .0674326   .0124417                      .0430472    .0918179
       /cut6 |   .3899425   .0126167                      .3652142    .4146708
       /cut7 |   .7487372   .0131098                      .7230424     .774432
       /cut8 |    1.31286   .0145612                       1.28432    1.341399
       /cut9 |   1.799088   .0166042                      1.766545    1.831632
------------------------------------------------------------------------------

. xi: ologit control trust i.codewb, robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

Iteration 0:   log pseudolikelihood = -84082.701  
Iteration 1:   log pseudolikelihood = -82146.102  
Iteration 2:   log pseudolikelihood =  -82131.34  
Iteration 3:   log pseudolikelihood = -82131.335  

Ordered logistic regression                       Number of obs   =      37222
                                                  Wald chi2(0)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -82131.335                 Pseudo R2       =     0.0232

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.2182721   .0353875    -6.17   0.000    -.2876304   -.1489139
  _Icodewb_2 |    .944899   .0390182    24.22   0.000     .8684248    1.021373
  _Icodewb_3 |   .7583975   .0323628    23.43   0.000     .6949675    .8218275
  _Icodewb_4 |   .4540551   .0147155    30.86   0.000     .4252133    .4828969
  _Icodewb_5 |   1.173819   .0477834    24.57   0.000     1.080165    1.267473
  _Icodewb_6 |   .5260733   .0191916    27.41   0.000     .4884585    .5636882
  _Icodewb_7 |   .3217315   .0141275    22.77   0.000     .2940422    .3494208
  _Icodewb_8 |   .8553929   .0332375    25.74   0.000     .7902487    .9205371
  _Icodewb_9 |    1.20977   .0511148    23.67   0.000     1.109587    1.309953
 _Icodewb_10 |   .4368568   .0159128    27.45   0.000     .4056684    .4680452
 _Icodewb_11 |   .4612634    .020418    22.59   0.000     .4212448     .501282
 _Icodewb_12 |   .4386898   .0179453    24.45   0.000     .4035175     .473862
 _Icodewb_13 |   .9911258   .0409546    24.20   0.000     .9108562    1.071395
 _Icodewb_14 |   .4993664   .0211249    23.64   0.000     .4579624    .5407704
 _Icodewb_15 |   1.582049    .061234    25.84   0.000     1.462033    1.702065
 _Icodewb_16 |    .594112   .0237347    25.03   0.000     .5475928    .6406312
 _Icodewb_17 |  -.3910352   .0139977   -27.94   0.000    -.4184701   -.3636002
 _Icodewb_18 |   .5115678   .0203998    25.08   0.000     .4715849    .5515508
 _Icodewb_19 |   .1718867   .0071131    24.16   0.000     .1579453     .185828
 _Icodewb_20 |   1.413227   .0547537    25.81   0.000     1.305912    1.520543
 _Icodewb_21 |   2.058288   .0784746    26.23   0.000     1.904481    2.212095
 _Icodewb_22 |   .5397727   .0233554    23.11   0.000     .4939969    .5855486
 _Icodewb_23 |   .9200772   .0360714    25.51   0.000     .8493786    .9907757
 _Icodewb_24 |    1.69177    .065188    25.95   0.000     1.564004    1.819536
 _Icodewb_25 |   .8390448   .0363445    23.09   0.000     .7678108    .9102788
 _Icodewb_26 |   1.380495   .0602803    22.90   0.000     1.262347    1.498642
 _Icodewb_27 |   1.299524   .0518527    25.06   0.000     1.197894    1.401153
 _Icodewb_28 |   1.859381   .0726346    25.60   0.000      1.71702    2.001742
 _Icodewb_29 |   .8761514   .0343621    25.50   0.000      .808803    .9434999
 _Icodewb_30 |   .0433435   .0115276     3.76   0.000     .0207497    .0659372
 _Icodewb_31 |   1.866724   .0740037    25.22   0.000     1.721679    2.011769
 _Icodewb_32 |   .8264063    .031975    25.85   0.000     .7637365    .8890761
-------------+----------------------------------------------------------------
       /cut1 |  -1.337483   .0590515                     -1.453221   -1.221744
       /cut2 |  -.7332075   .0326974                     -.7972932   -.6691218
       /cut3 |  -.1739878   .0186221                     -.2104865   -.1374891
       /cut4 |   .2232468   .0256082                      .1730556     .273438
       /cut5 |   .9761746   .0464549                      .8851246    1.067225
       /cut6 |   1.323159   .0616368                      1.202353    1.443965
       /cut7 |   1.708742   .0803646                      1.551231    1.866254
       /cut8 |   2.311063    .103592                      2.108026      2.5141
       /cut9 |   2.821885   .1091479                      2.607959    3.035811
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb, robust cluster(co
> dewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood = -71201.298  
Iteration 1:   log pseudolikelihood = -69091.756  
Iteration 2:   log pseudolikelihood = -69071.651  
Iteration 3:   log pseudolikelihood = -69071.642  
Iteration 4:   log pseudolikelihood = -69071.642  

Ordered logistic regression                       Number of obs   =      31489
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -69071.642                 Pseudo R2       =     0.0299

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1410821   .0390096    -3.62   0.000    -.2175394   -.0646247
         age |   1.394173   .4868621     2.86   0.004     .4399411    2.348405
        age2 |  -.9194764   .5348067    -1.72   0.086    -1.967678    .1287256
      female |   .1943786   .0243797     7.97   0.000     .1465952    .2421619
  highincome |  -.2787513   .0295119    -9.45   0.000    -.3365936    -.220909
   lowincome |   .1172006   .0311276     3.77   0.000     .0561916    .1782097
  highschool |  -.1416449   .0420245    -3.37   0.001    -.2240115   -.0592783
   lowschool |   .1857071   .0368932     5.03   0.000     .1133977    .2580165
      female |          0  (omitted)
  _Icodewb_2 |   1.063252   .0351294    30.27   0.000     .9943999    1.132105
  _Icodewb_3 |   .8425854   .0316826    26.59   0.000     .7804886    .9046822
  _Icodewb_4 |   .4419272    .016973    26.04   0.000     .4086607    .4751936
  _Icodewb_5 |   1.139821   .0459731    24.79   0.000     1.049715    1.229926
  _Icodewb_6 |   .3588472   .0220383    16.28   0.000     .3156529    .4020415
  _Icodewb_7 |   .2967533   .0153949    19.28   0.000     .2665798    .3269268
  _Icodewb_8 |    .830092   .0318507    26.06   0.000     .7676659    .8925182
  _Icodewb_9 |   1.330952   .0496914    26.78   0.000     1.233558    1.428345
 _Icodewb_10 |    .442075    .013549    32.63   0.000     .4155195    .4686305
 _Icodewb_11 |   .5000246   .0176121    28.39   0.000     .4655055    .5345437
 _Icodewb_12 |   .4327333   .0160676    26.93   0.000     .4012413    .4642252
 _Icodewb_13 |   1.136818   .0341848    33.26   0.000     1.069817    1.203819
 _Icodewb_14 |   .6598729   .0222262    29.69   0.000     .6163104    .7034354
 _Icodewb_15 |   1.572573   .0588516    26.72   0.000     1.457226     1.68792
 _Icodewb_16 |   .6202063   .0206663    30.01   0.000     .5797012    .6607115
 _Icodewb_17 |  -.3721627   .0239422   -15.54   0.000    -.4190886   -.3252369
 _Icodewb_18 |   .4954848   .0158989    31.16   0.000     .4643235    .5266461
 _Icodewb_19 |   .3937776   .0167094    23.57   0.000     .3610277    .4265275
 _Icodewb_20 |    1.49846   .0499745    29.98   0.000     1.400512    1.596409
 _Icodewb_21 |   2.069234   .0754407    27.43   0.000     1.921373    2.217095
 _Icodewb_22 |   .5586231   .0242068    23.08   0.000     .5111787    .6060674
 _Icodewb_23 |   .9334456   .0298414    31.28   0.000     .8749576    .9919336
 _Icodewb_24 |    1.61345   .0632978    25.49   0.000     1.489389    1.737511
 _Icodewb_25 |   .7926983   .0365031    21.72   0.000     .7211536    .8642429
 _Icodewb_26 |    1.43511   .0557813    25.73   0.000     1.325781     1.54444
 _Icodewb_27 |   1.378258   .0500067    27.56   0.000     1.280247     1.47627
 _Icodewb_28 |    1.96706   .0709477    27.73   0.000     1.828005    2.106115
 _Icodewb_29 |   .9756278   .0346082    28.19   0.000      .907797    1.043459
 _Icodewb_30 |   .0755313   .0218345     3.46   0.001     .0327365     .118326
 _Icodewb_31 |   1.903282   .0680687    27.96   0.000      1.76987    2.036694
 _Icodewb_32 |   .8889024   .0307332    28.92   0.000     .8286665    .9491383
-------------+----------------------------------------------------------------
       /cut1 |  -.8213572    .142212                     -1.100088   -.5426268
       /cut2 |   -.209629   .1253757                     -.4553608    .0361029
       /cut3 |   .3619018   .1149421                      .1366194    .5871843
       /cut4 |   .7645306   .1108686                      .5472321    .9818291
       /cut5 |   1.510729   .1206239                       1.27431    1.747147
       /cut6 |   1.859176   .1233353                      1.617443    2.100909
       /cut7 |   2.247108   .1331717                      1.986096    2.508119
       /cut8 |   2.859641   .1508714                      2.563939    3.155344
       /cut9 |   3.383232   .1514273                       3.08644    3.680024
------------------------------------------------------------------------------

. xi: ologit control trust insider age age2 female highincome lowincome highschool lowschool female i.codewb, robust cl
> uster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood =  -70964.24  
Iteration 1:   log pseudolikelihood = -68779.134  
Iteration 2:   log pseudolikelihood = -68757.369  
Iteration 3:   log pseudolikelihood = -68757.358  
Iteration 4:   log pseudolikelihood = -68757.358  

Ordered logistic regression                       Number of obs   =      31383
                                                  Wald chi2(8)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -68757.358                 Pseudo R2       =     0.0311

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1381648   .0390732    -3.54   0.000    -.2147469   -.0615828
     insider |  -.4513916   .0577796    -7.81   0.000    -.5646375   -.3381457
         age |   1.821459   .4802426     3.79   0.000     .8802014    2.762718
        age2 |  -1.317795   .5386273    -2.45   0.014    -2.373485   -.2621044
      female |    .161707   .0247206     6.54   0.000     .1132554    .2101585
  highincome |  -.2540506    .030236    -8.40   0.000    -.3133121   -.1947892
   lowincome |   .1159696   .0302394     3.84   0.000     .0567015    .1752377
  highschool |  -.1303587    .040717    -3.20   0.001    -.2101626   -.0505547
   lowschool |   .1751618   .0359145     4.88   0.000     .1047707    .2455528
      female |          0  (omitted)
  _Icodewb_2 |   1.095439   .0369532    29.64   0.000     1.023012    1.167865
  _Icodewb_3 |   .8346418   .0310502    26.88   0.000     .7737846    .8954991
  _Icodewb_4 |   .4389309   .0168271    26.08   0.000     .4059504    .4719115
  _Icodewb_5 |   1.142223   .0462154    24.72   0.000     1.051643    1.232804
  _Icodewb_6 |   .3531608   .0220247    16.03   0.000     .3099932    .3963285
  _Icodewb_7 |   .3129713   .0157245    19.90   0.000     .2821519    .3437907
  _Icodewb_8 |   .8337677    .032188    25.90   0.000     .7706803     .896855
  _Icodewb_9 |   1.337745   .0498592    26.83   0.000     1.240023    1.435467
 _Icodewb_10 |   .4535936   .0142457    31.84   0.000     .4256725    .4815146
 _Icodewb_11 |   .4920819   .0176913    27.81   0.000     .4574076    .5267562
 _Icodewb_12 |   .4440703   .0163901    27.09   0.000     .4119462    .4761944
 _Icodewb_13 |   1.149178   .0340617    33.74   0.000     1.082418    1.215937
 _Icodewb_14 |   .6380833   .0212346    30.05   0.000     .5964642    .6797024
 _Icodewb_15 |   1.572343   .0591962    26.56   0.000     1.456321    1.688366
 _Icodewb_16 |     .65647   .0227207    28.89   0.000     .6119382    .7010018
 _Icodewb_17 |  -.3207082   .0231614   -13.85   0.000    -.3661038   -.2753126
 _Icodewb_18 |   .5283064   .0180232    29.31   0.000     .4929816    .5636312
 _Icodewb_19 |   .3628473   .0157279    23.07   0.000     .3320212    .3936734
 _Icodewb_20 |   1.473511   .0493102    29.88   0.000     1.376865    1.570157
 _Icodewb_21 |   2.057909   .0750079    27.44   0.000     1.910896    2.204922
 _Icodewb_22 |   .5602411   .0241126    23.23   0.000     .5129813     .607501
 _Icodewb_23 |   .9420073   .0305342    30.85   0.000     .8821613    1.001853
 _Icodewb_24 |    1.61323   .0636672    25.34   0.000     1.488444    1.738015
 _Icodewb_25 |   .8122367   .0376136    21.59   0.000     .7385155     .885958
 _Icodewb_26 |   1.403967   .0545547    25.74   0.000     1.297042    1.510892
 _Icodewb_27 |   1.371643   .0494452    27.74   0.000     1.274732    1.468553
 _Icodewb_28 |   1.962769   .0707062    27.76   0.000     1.824188    2.101351
 _Icodewb_29 |   .9582229   .0337848    28.36   0.000     .8920058     1.02444
 _Icodewb_30 |   .0368263   .0219696     1.68   0.094    -.0062333    .0798859
 _Icodewb_31 |   1.943819   .0701887    27.69   0.000     1.806252    2.081387
 _Icodewb_32 |   .8864064   .0302358    29.32   0.000     .8271452    .9456675
-------------+----------------------------------------------------------------
       /cut1 |  -.7776297   .1385914                     -1.049264   -.5059957
       /cut2 |   -.163042   .1217423                     -.4016525    .0755685
       /cut3 |   .4106716   .1121611                      .1908399    .6305033
       /cut4 |   .8147309   .1089712                      .6011512    1.028311
       /cut5 |   1.562919   .1199919                      1.327739    1.798099
       /cut6 |   1.912204   .1236567                      1.669842    2.154567
       /cut7 |   2.300787   .1344393                      2.037291    2.564283
       /cut8 |   2.913975   .1528125                      2.614468    3.213482
       /cut9 |   3.438406   .1536903                      3.137178    3.739633
------------------------------------------------------------------------------

. xi: ologit control trust burpol incumbent age age2 female highincome lowincome highschool lowschool female i.codewb, 
> robust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
note: _Icodewb_30 omitted because of collinearity
note: _Icodewb_31 omitted because of collinearity
Iteration 0:   log pseudolikelihood = -51804.916  
Iteration 1:   log pseudolikelihood = -50218.142  
Iteration 2:   log pseudolikelihood = -50202.107  
Iteration 3:   log pseudolikelihood = -50202.099  
Iteration 4:   log pseudolikelihood = -50202.099  

Ordered logistic regression                       Number of obs   =      22901
                                                  Wald chi2(9)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -50202.099                 Pseudo R2       =     0.0309

                                (Std. Err. adjusted for 30 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1504497   .0457816    -3.29   0.001    -.2401799   -.0607195
      burpol |    .019915   .1786637     0.11   0.911    -.3302595    .3700894
   incumbent |  -.4988579   .0604936    -8.25   0.000    -.6174232   -.3802927
         age |    1.59782   .5889857     2.71   0.007     .4434294    2.752211
        age2 |  -.9927758   .6420517    -1.55   0.122    -2.251174    .2656224
      female |    .170073   .0260224     6.54   0.000     .1190701     .221076
  highincome |  -.2059046   .0380121    -5.42   0.000     -.280407   -.1314022
   lowincome |   .1066391   .0388445     2.75   0.006     .0305052     .182773
  highschool |  -.1486787   .0463372    -3.21   0.001     -.239498   -.0578594
   lowschool |   .1892584   .0353701     5.35   0.000     .1199343    .2585824
      female |          0  (omitted)
  _Icodewb_2 |   1.114519   .0309587    36.00   0.000     1.053841    1.175197
  _Icodewb_3 |   .8353847   .0296751    28.15   0.000     .7772226    .8935469
  _Icodewb_4 |   .4867506    .016972    28.68   0.000     .4534861    .5200151
  _Icodewb_5 |   1.118819   .0430498    25.99   0.000     1.034443    1.203195
  _Icodewb_6 |    .308653   .0239597    12.88   0.000     .2616928    .3556131
  _Icodewb_7 |   .3109291   .0191921    16.20   0.000     .2733133    .3485449
  _Icodewb_8 |    .912332    .028624    31.87   0.000     .8562301    .9684339
  _Icodewb_9 |   1.355036    .045269    29.93   0.000      1.26631    1.443761
 _Icodewb_10 |   .4485814   .0154911    28.96   0.000     .4182194    .4789434
 _Icodewb_11 |    .479876    .016736    28.67   0.000     .4470741    .5126779
 _Icodewb_12 |   .4651795    .015637    29.75   0.000     .4345315    .4958275
 _Icodewb_13 |   1.117182   .0324802    34.40   0.000     1.053522    1.180842
 _Icodewb_14 |   .7235095   .0188539    38.37   0.000     .6865565    .7604624
 _Icodewb_15 |    1.59357   .0551184    28.91   0.000      1.48554      1.7016
 _Icodewb_16 |   .7605076   .0200682    37.90   0.000     .7211746    .7998406
 _Icodewb_17 |  -.3043075   .0246746   -12.33   0.000    -.3526688   -.2559462
 _Icodewb_18 |   .5718472    .016914    33.81   0.000     .5386963    .6049981
 _Icodewb_19 |   .3963727     .01578    25.12   0.000     .3654445    .4273009
 _Icodewb_20 |   1.396847   .0379056    36.85   0.000     1.322554    1.471141
 _Icodewb_21 |   2.125446   .0706257    30.09   0.000     1.987022     2.26387
 _Icodewb_22 |   .6012209   .0206723    29.08   0.000     .5607039    .6417378
 _Icodewb_23 |   1.029096   .0285642    36.03   0.000      .973111    1.085081
 _Icodewb_24 |    1.67218   .0616114    27.14   0.000     1.551424    1.792936
 _Icodewb_25 |   .8246847   .0340655    24.21   0.000     .7579175    .8914519
 _Icodewb_26 |   1.273263   .0400201    31.82   0.000     1.194825    1.351701
 _Icodewb_27 |   1.442113   .0461689    31.24   0.000     1.351624    1.532602
 _Icodewb_28 |   1.942202   .0630608    30.80   0.000     1.818605    2.065799
 _Icodewb_29 |   1.011801   .0319625    31.66   0.000     .9491558    1.074446
 _Icodewb_30 |          0  (omitted)
 _Icodewb_31 |          0  (omitted)
 _Icodewb_32 |   .9851126   .0324092    30.40   0.000     .9215917    1.048633
-------------+----------------------------------------------------------------
       /cut1 |  -.7645921   .1596872                     -1.077573   -.4516109
       /cut2 |  -.1512856    .144939                     -.4353609    .1327897
       /cut3 |   .4206176   .1358313                      .1543932    .6868421
       /cut4 |    .815718   .1308028                      .5593492    1.072087
       /cut5 |   1.555898    .136163                      1.289024    1.822773
       /cut6 |   1.903576   .1354195                      1.638159    2.168994
       /cut7 |   2.300715   .1394919                      2.027316    2.574115
       /cut8 |   2.922708   .1542568                      2.620371    3.225046
       /cut9 |   3.443146   .1512149                      3.146771    3.739522
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb if insider==0, rob
> ust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood =  -64140.85  
Iteration 1:   log pseudolikelihood = -62267.115  
Iteration 2:   log pseudolikelihood = -62249.897  
Iteration 3:   log pseudolikelihood = -62249.889  
Iteration 4:   log pseudolikelihood = -62249.889  

Ordered logistic regression                       Number of obs   =      28370
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -62249.889                 Pseudo R2       =     0.0295

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.1567917   .0383956    -4.08   0.000    -.2320458   -.0815376
         age |   2.024758   .5002539     4.05   0.000     1.044278    3.005238
        age2 |  -1.571147    .542922    -2.89   0.004    -2.635254    -.507039
      female |   .1491248   .0249325     5.98   0.000      .100258    .1979915
  highincome |  -.2400633   .0301559    -7.96   0.000    -.2991677   -.1809588
   lowincome |   .1060221   .0296518     3.58   0.000     .0479057    .1641385
  highschool |   -.182725   .0400631    -4.56   0.000    -.2612473   -.1042027
   lowschool |   .1808763    .038391     4.71   0.000     .1056313    .2561214
      female |          0  (omitted)
  _Icodewb_2 |   1.134692   .0385115    29.46   0.000     1.059211    1.210173
  _Icodewb_3 |   .8599021   .0339441    25.33   0.000     .7933729    .9264313
  _Icodewb_4 |   .4524115   .0187215    24.17   0.000      .415718     .489105
  _Icodewb_5 |   1.163335   .0475449    24.47   0.000     1.070149    1.256522
  _Icodewb_6 |   .3474123   .0222271    15.63   0.000      .303848    .3909765
  _Icodewb_7 |   .3407962    .015849    21.50   0.000     .3097328    .3718596
  _Icodewb_8 |    .816925   .0322673    25.32   0.000     .7536822    .8801678
  _Icodewb_9 |   1.345353   .0514162    26.17   0.000      1.24458    1.446127
 _Icodewb_10 |   .4555649   .0152835    29.81   0.000     .4256097    .4855201
 _Icodewb_11 |    .520826   .0185293    28.11   0.000     .4845092    .5571429
 _Icodewb_12 |   .4165765   .0166056    25.09   0.000     .3840301    .4491228
 _Icodewb_13 |   1.168049   .0352401    33.15   0.000      1.09898    1.237118
 _Icodewb_14 |   .6335801   .0214874    29.49   0.000     .5914657    .6756945
 _Icodewb_15 |   1.573767   .0598163    26.31   0.000     1.456529    1.691005
 _Icodewb_16 |   .5715043    .021213    26.94   0.000     .5299276    .6130811
 _Icodewb_17 |  -.3943853   .0244312   -16.14   0.000    -.4422694   -.3465011
 _Icodewb_18 |   .5456431   .0187196    29.15   0.000     .5089533    .5823328
 _Icodewb_19 |   .3214369   .0175686    18.30   0.000     .2870032    .3558706
 _Icodewb_20 |   1.473056   .0492611    29.90   0.000     1.376506    1.569605
 _Icodewb_21 |   2.063723   .0752924    27.41   0.000     1.916153    2.211293
 _Icodewb_22 |   .5306591   .0237736    22.32   0.000     .4840638    .5772544
 _Icodewb_23 |   .9192568   .0318451    28.87   0.000     .8568415    .9816722
 _Icodewb_24 |    1.62899   .0637213    25.56   0.000     1.504098    1.753881
 _Icodewb_25 |   .7686019   .0359884    21.36   0.000     .6980659    .8391379
 _Icodewb_26 |   1.425323    .054774    26.02   0.000     1.317968    1.532678
 _Icodewb_27 |   1.331055   .0494219    26.93   0.000      1.23419     1.42792
 _Icodewb_28 |   1.966936   .0707156    27.81   0.000     1.828336    2.105536
 _Icodewb_29 |   .9663907   .0351472    27.50   0.000     .8975034    1.035278
 _Icodewb_30 |      .0507   .0231957     2.19   0.029     .0052372    .0961628
 _Icodewb_31 |   1.911124   .0678786    28.16   0.000     1.778085    2.044164
 _Icodewb_32 |   .9152827   .0326171    28.06   0.000     .8513544     .979211
-------------+----------------------------------------------------------------
       /cut1 |  -.7705744   .1477756                     -1.060209   -.4809394
       /cut2 |  -.1629095   .1310089                     -.4196821    .0938632
       /cut3 |   .4092729   .1193064                      .1754368    .6431091
       /cut4 |   .8188156   .1146096                      .5941848    1.043446
       /cut5 |   1.573384   .1256099                      1.327193    1.819575
       /cut6 |   1.923951   .1277786                      1.673509    2.174392
       /cut7 |   2.316391   .1367588                      2.048348    2.584433
       /cut8 |   2.933954    .153119                      2.633846    3.234061
       /cut9 |   3.468543   .1519556                      3.170715    3.766371
------------------------------------------------------------------------------

. xi: ologit control trust age age2 female highincome lowincome highschool lowschool female i.codewb if insider==1, rob
> ust cluster(codewb)
i.codewb          _Icodewb_1-32       (_Icodewb_1 for codewb==AUT omitted)

note: female omitted because of collinearity
Iteration 0:   log pseudolikelihood =  -6658.056  
Iteration 1:   log pseudolikelihood = -6429.6916  
Iteration 2:   log pseudolikelihood = -6427.2995  
Iteration 3:   log pseudolikelihood = -6427.2977  
Iteration 4:   log pseudolikelihood = -6427.2977  

Ordered logistic regression                       Number of obs   =       3013
                                                  Wald chi2(7)    =          .
                                                  Prob > chi2     =          .
Log pseudolikelihood = -6427.2977                 Pseudo R2       =     0.0347

                                (Std. Err. adjusted for 32 clusters in codewb)
------------------------------------------------------------------------------
             |               Robust
     control |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.0044621   .0781689    -0.06   0.954    -.1576703    .1487461
         age |  -.6511355   1.667592    -0.39   0.696    -3.919556    2.617285
        age2 |   1.715779   1.701033     1.01   0.313    -1.618184    5.049742
      female |   .3637243   .0833992     4.36   0.000      .200265    .5271837
  highincome |   -.332508   .0804104    -4.14   0.000    -.4901094   -.1749065
   lowincome |    .299606   .0786992     3.81   0.000     .1453584    .4538535
  highschool |   .2322475   .0911234     2.55   0.011     .0536489    .4108461
   lowschool |   .0988914   .1337591     0.74   0.460    -.1632716    .3610544
      female |          0  (omitted)
  _Icodewb_2 |   .8619472   .0477701    18.04   0.000     .7683195    .9555749
  _Icodewb_3 |   .7095668    .043077    16.47   0.000     .6251374    .7939962
  _Icodewb_4 |   .2923861   .0535935     5.46   0.000     .1873448    .3974273
  _Icodewb_5 |   .9590001    .049583    19.34   0.000     .8618191    1.056181
  _Icodewb_6 |    .411485   .0381763    10.78   0.000     .3366608    .4863091
  _Icodewb_7 |   .2086124    .039576     5.27   0.000      .131045    .2861799
  _Icodewb_8 |   1.120222   .0548067    20.44   0.000     1.012803    1.227641
  _Icodewb_9 |   1.303731   .0698516    18.66   0.000     1.166824    1.440637
 _Icodewb_10 |   .5611872   .0228147    24.60   0.000     .5164712    .6059032
 _Icodewb_11 |   .1175433   .0356777     3.29   0.001     .0476163    .1874702
 _Icodewb_12 |   .7354844   .0442878    16.61   0.000      .648682    .8222868
 _Icodewb_13 |   1.093301     .06962    15.70   0.000     .9568483    1.229754
 _Icodewb_14 |   .7275943   .0518036    14.05   0.000      .626061    .8291275
 _Icodewb_15 |    1.56498   .0721424    21.69   0.000     1.423584    1.706376
 _Icodewb_16 |   1.236205   .0569743    21.70   0.000     1.124537    1.347872
 _Icodewb_17 |   .0036069   .0234617     0.15   0.878    -.0423772     .049591
 _Icodewb_18 |   .4959818   .0352771    14.06   0.000     .4268399    .5651236
 _Icodewb_19 |   1.237727   .0675386    18.33   0.000     1.105353      1.3701
 _Icodewb_20 |   1.440992   .0727503    19.81   0.000     1.298404     1.58358
 _Icodewb_21 |   2.031774    .106081    19.15   0.000      1.82386    2.239689
 _Icodewb_22 |   .9593767   .0532578    18.01   0.000     .8549933     1.06376
 _Icodewb_23 |   1.154764   .0552766    20.89   0.000     1.046424    1.263104
 _Icodewb_24 |   1.434343   .0838651    17.10   0.000     1.269971    1.598716
 _Icodewb_25 |   1.265431   .0721338    17.54   0.000     1.124052    1.406811
 _Icodewb_26 |   .7985266   .0649692    12.29   0.000     .6711893    .9258639
 _Icodewb_27 |   1.862212   .0882094    21.11   0.000     1.689325      2.0351
 _Icodewb_28 |   1.956203   .0988187    19.80   0.000     1.762521    2.149884
 _Icodewb_29 |   .7536178   .0504708    14.93   0.000      .654697    .8525387
 _Icodewb_30 |  -.2918843   .0345684    -8.44   0.000    -.3596371   -.2241315
 _Icodewb_31 |   2.254072   .1600756    14.08   0.000     1.940329    2.567814
 _Icodewb_32 |   .5872444   .0385732    15.22   0.000     .5116422    .6628465
-------------+----------------------------------------------------------------
       /cut1 |  -.4956404   .4375314                     -1.353186    .3619055
       /cut2 |   .1805953   .4391613                     -.6801449    1.041336
       /cut3 |   .7840265   .4408308                      -.079986    1.648039
       /cut4 |   1.156076   .4367365                      .3000879    2.012063
       /cut5 |   1.865261   .4480877                      .9870255    2.743497
       /cut6 |   2.209493   .4589575                      1.309953    3.109033
       /cut7 |   2.561569   .4641611                       1.65183    3.471308
       /cut8 |   3.129801   .4956765                      2.158293    4.101309
       /cut9 |   3.530286   .5018554                      2.546667    4.513904
------------------------------------------------------------------------------

. 
. 
. ****** FIGURE 1 *******
. tab control if trust==0

        firms: freedom(1) - control(10) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
state should give more freedom to firms |      3,210       12.29       12.29
                                      2 |      1,816        6.95       19.24
                                      3 |      2,217        8.49       27.73
                                      4 |      1,943        7.44       35.17
                                      5 |      4,282       16.39       51.56
                                      6 |      1,911        7.32       58.88
                                      7 |      1,994        7.63       66.51
                                      8 |      2,835       10.85       77.37
                                      9 |      1,958        7.50       84.87
state should control firms more effecti |      3,953       15.13      100.00
----------------------------------------+-----------------------------------
                                  Total |     26,119      100.00

. tab control if trust==1

        firms: freedom(1) - control(10) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
state should give more freedom to firms |      1,280       11.53       11.53
                                      2 |      1,067        9.61       21.14
                                      3 |      1,428       12.86       34.00
                                      4 |      1,136       10.23       44.23
                                      5 |      2,093       18.85       63.08
                                      6 |        959        8.64       71.72
                                      7 |        930        8.38       80.10
                                      8 |        946        8.52       88.62
                                      9 |        434        3.91       92.52
state should control firms more effecti |        830        7.48      100.00
----------------------------------------+-----------------------------------
                                  Total |     11,103      100.00

. 
. ****** FIGURE 1 *******
. tab control if burpol==1

        firms: freedom(1) - control(10) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
state should give more freedom to firms |         30       15.08       15.08
                                      2 |         24       12.06       27.14
                                      3 |         31       15.58       42.71
                                      4 |         17        8.54       51.26
                                      5 |         32       16.08       67.34
                                      6 |          9        4.52       71.86
                                      7 |         14        7.04       78.89
                                      8 |         13        6.53       85.43
                                      9 |         10        5.03       90.45
state should control firms more effecti |         19        9.55      100.00
----------------------------------------+-----------------------------------
                                  Total |        199      100.00

. tab control if incumbent==1

        firms: freedom(1) - control(10) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
state should give more freedom to firms |        706       20.15       20.15
                                      2 |        402       11.47       31.62
                                      3 |        427       12.19       43.81
                                      4 |        295        8.42       52.23
                                      5 |        539       15.38       67.61
                                      6 |        233        6.65       74.26
                                      7 |        205        5.85       80.11
                                      8 |        252        7.19       87.30
                                      9 |        123        3.51       90.81
state should control firms more effecti |        322        9.19      100.00
----------------------------------------+-----------------------------------
                                  Total |      3,504      100.00

. tab control if insider==0

        firms: freedom(1) - control(10) |      Freq.     Percent        Cum.
----------------------------------------+-----------------------------------
state should give more freedom to firms |      3,745       11.21       11.21
                                      2 |      2,454        7.35       18.56
                                      3 |      3,170        9.49       28.05
                                      4 |      2,753        8.24       36.29
                                      5 |      5,769       17.27       53.56
                                      6 |      2,617        7.83       61.40
                                      7 |      2,696        8.07       69.47
                                      8 |      3,506       10.50       79.97
                                      9 |      2,255        6.75       86.72
state should control firms more effecti |      4,437       13.28      100.00
----------------------------------------+-----------------------------------
                                  Total |     33,402      100.00

. 
. 
. ********************************** CROSS-COUNTRY RESULTS **********************************
. collapse control, by(codewb)

. rename control demand_for_regulation

. 
. merge m:1 codewb using crosscountry
codewb was str3 now str6

    Result                           # of obs.
    -----------------------------------------
    not matched                           187
        from master                         0  (_merge==1)
        from using                        187  (_merge==2)

    matched                                32  (_merge==3)
    -----------------------------------------

. drop _m

. 
. 
. ****** TABLE 3 *******
. pwcorr entry costs_of_procedures trust lngdp99 lnpop99 water_pollution unofficial_economy, sig

             |    entry costs_~s    trust  lngdp99  lnpop99 water_~n unoffi~y
-------------+---------------------------------------------------------------
       entry |   1.0000 
             |
             |
costs_of_p~s |  -0.2913   1.0000 
             |   0.0072
             |
       trust |  -0.6226   0.3259   1.0000 
             |   0.0000   0.0196
             |
     lngdp99 |  -0.4745   0.7529   0.5172   1.0000 
             |   0.0000   0.0000   0.0001
             |
     lnpop99 |   0.2533  -0.2036  -0.0373  -0.1145   1.0000 
             |   0.0201   0.0649   0.7970   0.2998
             |
water_poll~n |   0.1571  -0.2555  -0.1375  -0.4788  -0.1320   1.0000 
             |   0.1752   0.0259   0.3463   0.0000   0.2557
             |
unofficial~y |   0.4982  -0.3827  -0.6138  -0.7306   0.0797   0.5377   1.0000 
             |   0.0000   0.0008   0.0000   0.0000   0.5057   0.0000
             |

. sum entry costs_of_procedures trust lngdp99 lnpop99 water_pollution unofficial_economy

    Variable |       Obs        Mean    Std. Dev.       Min        Max
-------------+--------------------------------------------------------
       entry |        85    2.242589    .5050469   .6931472   3.044523
costs_of_p~s |        84    4.157481    1.414741   .8407047   6.973231
       trust |        51    .3042726    .1531118   .0462991   .6517354
     lngdp99 |        85    7.949139    1.637988   5.247024   10.55451
     lnpop99 |       197    15.33689    2.092972    10.6516   20.94939
-------------+--------------------------------------------------------
water_poll~n |        76    .1837303    .0412268         .1      .3151
unofficial~y |        73    28.89075    15.30712        8.6       68.8

. 
. ****** TABLE 4 *******
. reg entry trust, r

Linear regression                                      Number of obs =      51
                                                       F(  1,    49) =   27.16
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3876
                                                       Root MSE      =  .42953

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -2.209557   .4239804    -5.21   0.000    -3.061577   -1.357536
       _cons |   2.848865   .1104989    25.78   0.000     2.626809    3.070921
------------------------------------------------------------------------------

. reg entry trust lngdp99, r

Linear regression                                      Number of obs =      51
                                                       F(  2,    48) =   16.61
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4196
                                                       Root MSE      =  .42251

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -1.826323   .4491571    -4.07   0.000    -2.729414   -.9232318
     lngdp99 |  -.0827598   .0488277    -1.69   0.097    -.1809344    .0154147
       _cons |   3.449065   .3685279     9.36   0.000      2.70809     4.19004
------------------------------------------------------------------------------

. reg entry trust lngdp99 lnpop99, r

Linear regression                                      Number of obs =      50
                                                       F(  3,    46) =   13.58
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.4682
                                                       Root MSE      =  .41301

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -1.937383    .394185    -4.91   0.000    -2.730836    -1.14393
     lngdp99 |  -.0536866   .0469177    -1.14   0.258    -.1481271    .0407538
     lnpop99 |   .0810842   .0352943     2.30   0.026     .0100404     .152128
       _cons |   1.856595   .7811483     2.38   0.022     .2842255    3.428965
------------------------------------------------------------------------------

. reg demand_for_regulation trust, r

Linear regression                                      Number of obs =      25
                                                       F(  1,    23) =   29.07
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3985
                                                       Root MSE      =  .75633

------------------------------------------------------------------------------
             |               Robust
demand_for~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -4.453921   .8260211    -5.39   0.000    -6.162676   -2.745166
       _cons |    6.91967   .3630872    19.06   0.000     6.168567    7.670773
------------------------------------------------------------------------------

. reg demand_for_regulation trust lngdp99, r

Linear regression                                      Number of obs =      25
                                                       F(  2,    22) =   15.06
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4747
                                                       Root MSE      =  .72265

------------------------------------------------------------------------------
             |               Robust
demand_for~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |   -2.98155   1.020175    -2.92   0.008    -5.097264   -.8658366
     lngdp99 |  -.2842613   .1586929    -1.79   0.087    -.6133702    .0448475
       _cons |   8.991717   1.303335     6.90   0.000     6.288766    11.69467
------------------------------------------------------------------------------

. reg demand_for_regulation trust lngdp99 lnpop99, r

Linear regression                                      Number of obs =      25
                                                       F(  3,    21) =   12.38
                                                       Prob > F      =  0.0001
                                                       R-squared     =  0.4748
                                                       Root MSE      =  .73963

------------------------------------------------------------------------------
             |               Robust
demand_for~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -2.990146   1.117537    -2.68   0.014    -5.314192      -.6661
     lngdp99 |   -.283834   .1601102    -1.77   0.091    -.6168015    .0491335
     lnpop99 |  -.0046772   .1269376    -0.04   0.971    -.2686585     .259304
       _cons |     9.0678   2.809917     3.23   0.004     3.224258    14.91134
------------------------------------------------------------------------------

. 
. ****** TABLE 5 *******
. reg costs_of_procedures trust, r

Linear regression                                      Number of obs =      51
                                                       F(  1,    49) =    5.92
                                                       Prob > F      =  0.0187
                                                       R-squared     =  0.1062
                                                       Root MSE      =   1.266

------------------------------------------------------------------------------
             |               Robust
costs_of_p~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |   2.821586    1.16007     2.43   0.019     .4903379    5.152834
       _cons |   3.590125   .3491794    10.28   0.000     2.888423    4.291827
------------------------------------------------------------------------------

. reg costs_of_procedures trust lngdp99, r

Linear regression                                      Number of obs =      51
                                                       F(  2,    48) =   22.40
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5410
                                                       Root MSE      =  .91669

------------------------------------------------------------------------------
             |               Robust
costs_of_p~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.6279348   .8128105    -0.77   0.444      -2.2622     1.00633
     lngdp99 |   .7449281   .1134024     6.57   0.000     .5169174    .9729389
       _cons |  -1.812324    .951262    -1.91   0.063    -3.724964    .1003162
------------------------------------------------------------------------------

. reg costs_of_procedures trust lngdp99 lnpop99, r

Linear regression                                      Number of obs =      50
                                                       F(  3,    46) =   14.05
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5521
                                                       Root MSE      =  .92462

------------------------------------------------------------------------------
             |               Robust
costs_of_p~s |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.4957462   .8312781    -0.60   0.554    -2.169022     1.17753
     lngdp99 |   .7135353   .1243482     5.74   0.000     .4632353    .9638353
     lnpop99 |  -.0914038   .0967544    -0.94   0.350    -.2861603    .1033528
       _cons |  -.0273057   2.156265    -0.01   0.990    -4.367642    4.313031
------------------------------------------------------------------------------

. reg time_to_complete trust, r

Linear regression                                      Number of obs =      51
                                                       F(  1,    49) =    6.14
                                                       Prob > F      =  0.0167
                                                       R-squared     =  0.1412
                                                       Root MSE      =  .56853

------------------------------------------------------------------------------
             |               Robust
time_to_co~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -1.490682   .6014412    -2.48   0.017    -2.699323   -.2820403
       _cons |   1.709601   .1596546    10.71   0.000     1.388763    2.030439
------------------------------------------------------------------------------

. reg time_to_complete trust lngdp99, r

Linear regression                                      Number of obs =      51
                                                       F(  2,    48) =    5.66
                                                       Prob > F      =  0.0062
                                                       R-squared     =  0.2057
                                                       Root MSE      =  .55243

------------------------------------------------------------------------------
             |               Robust
time_to_co~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.8819395   .6475839    -1.36   0.180    -2.183994    .4201153
     lngdp99 |  -.1314586   .0625579    -2.10   0.041    -.2572398   -.0056775
       _cons |    2.66298   .4684703     5.68   0.000     1.721057    3.604902
------------------------------------------------------------------------------

. reg time_to_complete trust lngdp99 lnpop99, r

Linear regression                                      Number of obs =      50
                                                       F(  3,    46) =    4.13
                                                       Prob > F      =  0.0113
                                                       R-squared     =  0.2182
                                                       Root MSE      =  .55869

------------------------------------------------------------------------------
             |               Robust
time_to_co~e |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       trust |  -.8622481   .6723691    -1.28   0.206    -2.215657    .4911607
     lngdp99 |  -.1446469   .0656371    -2.20   0.033    -.2767675   -.0125263
     lnpop99 |    -.02715   .0539948    -0.50   0.617    -.1358359    .0815359
       _cons |   3.221526   1.073216     3.00   0.004     1.061254    5.381798
------------------------------------------------------------------------------

. 
. 
. ****** TABLE 6 *******
. reg water_pollution entry, r

Linear regression                                      Number of obs =      76
                                                       F(  1,    74) =    2.30
                                                       Prob > F      =  0.1339
                                                       R-squared     =  0.0247
                                                       Root MSE      =  .04099

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   .0127279   .0083973     1.52   0.134    -.0040041      .02946
       _cons |    .155709   .0174298     8.93   0.000     .1209793    .1904386
------------------------------------------------------------------------------

. reg water_pollution entry trust, r

Linear regression                                      Number of obs =      49
                                                       F(  2,    46) =    4.78
                                                       Prob > F      =  0.0130
                                                       R-squared     =  0.1015
                                                       Root MSE      =  .02762

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0189156    .006898    -2.74   0.009    -.0328006   -.0050306
       trust |  -.0669466   .0260114    -2.57   0.013    -.1193048   -.0145884
       _cons |   .2337558   .0199614    11.71   0.000     .1935756     .273936
------------------------------------------------------------------------------

. gen reducedsample=e(sample)

. reg water_pollution entry if reducedsample==1, r

Linear regression                                      Number of obs =      49
                                                       F(  1,    47) =    1.42
                                                       Prob > F      =  0.2401
                                                       R-squared     =  0.0198
                                                       Root MSE      =  .02854

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0072848   .0061229    -1.19   0.240    -.0196025     .005033
       _cons |   .1880859   .0126515    14.87   0.000     .1626344    .2135374
------------------------------------------------------------------------------

. reg water_pollution entry lngdp99, r

Linear regression                                      Number of obs =      76
                                                       F(  2,    73) =   12.25
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2310
                                                       Root MSE      =  .03665

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0036822   .0075761    -0.49   0.628    -.0187813    .0114169
     lngdp99 |   -.013097   .0026721    -4.90   0.000    -.0184225   -.0077714
       _cons |   .2983569   .0313734     9.51   0.000     .2358299    .3608839
------------------------------------------------------------------------------

. reg water_pollution entry trust lngdp99, r

Linear regression                                      Number of obs =      49
                                                       F(  3,    45) =    4.82
                                                       Prob > F      =  0.0054
                                                       R-squared     =  0.1621
                                                       Root MSE      =  .02697

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0226807   .0071024    -3.19   0.003    -.0369856   -.0083759
       trust |  -.0479431   .0311833    -1.54   0.131    -.1107494    .0148632
     lngdp99 |  -.0061657    .003098    -1.99   0.053    -.0124054    .0000741
       _cons |   .2897098   .0327724     8.84   0.000     .2237029    .3557168
------------------------------------------------------------------------------

. reg unofficial_economy entry, r

Linear regression                                      Number of obs =      73
                                                       F(  1,    71) =   32.97
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2482
                                                       Root MSE      =  13.365

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   14.75528   2.569844     5.74   0.000     9.631155     19.8794
       _cons |  -3.798194   5.213888    -0.73   0.469    -14.19439    6.598003
------------------------------------------------------------------------------

. reg unofficial_economy entry trust, r

Linear regression                                      Number of obs =      50
                                                       F(  2,    47) =   21.84
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.3812
                                                       Root MSE      =  9.5935

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   1.951908   2.682303     0.73   0.470    -3.444189    7.348005
       trust |  -44.11779   12.60879    -3.50   0.001     -69.4834   -18.75217
       _cons |   33.03084   9.490913     3.48   0.001     13.93759    52.12409
------------------------------------------------------------------------------

. replace reducedsample=e(sample)
(3 real changes made)

. reg unofficial_economy entry if reducedsample==1, r

Linear regression                                      Number of obs =      50
                                                       F(  1,    48) =   35.35
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.2093
                                                       Root MSE      =  10.731

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   9.987779   1.679977     5.95   0.000      6.60996     13.3656
       _cons |   2.394419   3.430029     0.70   0.488    -4.502116    9.290954
------------------------------------------------------------------------------

. reg unofficial_economy entry lngdp99, r

Linear regression                                      Number of obs =      73
                                                       F(  2,    70) =   44.63
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.5607
                                                       Root MSE      =   10.29

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   5.559819   2.452823     2.27   0.027      .667817    10.45182
     lngdp99 |  -6.343412   .9960037    -6.37   0.000    -8.329879   -4.356945
       _cons |   68.88075   12.72715     5.41   0.000     43.49724    94.26426
------------------------------------------------------------------------------

. reg unofficial_economy entry trust lngdp99, r

Linear regression                                      Number of obs =      50
                                                       F(  3,    46) =   31.40
                                                       Prob > F      =  0.0000
                                                       R-squared     =  0.6607
                                                       Root MSE      =  7.1801

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   .0612496   2.262493     0.03   0.979    -4.492914    4.615413
       trust |  -17.06692   12.20204    -1.40   0.169    -41.62836    7.494517
     lngdp99 |  -5.860855   1.147628    -5.11   0.000    -8.170911     -3.5508
       _cons |   80.04078   11.74939     6.81   0.000      56.3905    103.6911
------------------------------------------------------------------------------

. 
. ****** TABLE 7 *******
. ivreg2 water_pollution (entry=lnpop99), r first 

First-stage regressions
-----------------------

First-stage regression of entry:

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       76
                                                      F(  1,    74) =     8.20
                                                      Prob > F      =   0.0055
Total (centered) SS     =  19.43051254                Centered R2   =   0.0828
Total (uncentered) SS   =  387.7925106                Uncentered R2 =   0.9540
Residual SS             =  17.82073295                Root MSE      =    .4907

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lnpop99 |   .1037548   .0362405     2.86   0.005     .0315441    .1759656
       _cons |   .4645721    .612116     0.76   0.450    -.7550957     1.68424
------------------------------------------------------------------------------
Included instruments: lnpop99
------------------------------------------------------------------------------
F test of excluded instruments:
  F(  1,    74) =     8.20
  Prob > F      =   0.0055
Angrist-Pischke multivariate F test of excluded instruments:
  F(  1,    74) =     8.20
  Prob > F      =   0.0055



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,    74)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    74)
entry        |       8.20    0.0055 |        8.42   0.0037 |        8.20

NB: first-stage test statistics heteroskedasticity-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=7.93     P-val=0.0049

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                       6.68
Kleibergen-Paap Wald rk F statistic                                 8.20

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,74)=        1.71     P-val=0.1952
Anderson-Rubin Wald test           Chi-sq(1)=      1.75     P-val=0.1853
Stock-Wright LM S statistic        Chi-sq(1)=      1.59     P-val=0.2068

NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity-robust

Number of observations               N  =         76
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          2
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       76
                                                      F(  1,    74) =     1.34
                                                      Prob > F      =   0.2505
Total (centered) SS     =  .1274733778                Centered R2   =  -0.3545
Total (uncentered) SS   =  2.692990899                Uncentered R2 =   0.9359
Residual SS             =  .1726582783                Root MSE      =   .04766

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0371465   .0316482    -1.17   0.241    -.0991759    .0248828
       _cons |   .2655106   .0711878     3.73   0.000     .1259851    .4050361
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):              7.927
                                                   Chi-sq(1) P-val =    0.0049
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):                6.685
                         (Kleibergen-Paap rk Wald F statistic):          8.197
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         entry
Excluded instruments: lnpop99
------------------------------------------------------------------------------

. ivreg2 water_pollution lngdp99 (entry=lnpop99), r first 

First-stage regressions
-----------------------

First-stage regression of entry:

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       76
                                                      F(  2,    73) =    11.23
                                                      Prob > F      =   0.0001
Total (centered) SS     =  19.43051254                Centered R2   =   0.2186
Total (uncentered) SS   =  387.7925106                Uncentered R2 =   0.9608
Residual SS             =  15.18354572                Root MSE      =    .4561

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lngdp99 |  -.1211587   .0374615    -3.23   0.002    -.1958193    -.046498
     lnpop99 |   .0836115   .0373195     2.24   0.028     .0092339    .1579891
       _cons |   1.787203    .769745     2.32   0.023     .2531039    3.321303
------------------------------------------------------------------------------
Included instruments: lngdp99 lnpop99
------------------------------------------------------------------------------
F test of excluded instruments:
  F(  1,    73) =     5.02
  Prob > F      =   0.0281
Angrist-Pischke multivariate F test of excluded instruments:
  F(  1,    73) =     5.02
  Prob > F      =   0.0281



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,    73)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    73)
entry        |       5.02    0.0281 |        5.23   0.0223 |        5.02

NB: first-stage test statistics heteroskedasticity-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=5.40     P-val=0.0201

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                       4.91
Kleibergen-Paap Wald rk F statistic                                 5.02

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,73)=        4.56     P-val=0.0361
Anderson-Rubin Wald test           Chi-sq(1)=      4.75     P-val=0.0293
Stock-Wright LM S statistic        Chi-sq(1)=      3.73     P-val=0.0535

NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity-robust

Number of observations               N  =         76
Number of regressors                 K  =          3
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          3
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       76
                                                      F(  2,    73) =     5.78
                                                      Prob > F      =   0.0047
Total (centered) SS     =  .1274733778                Centered R2   =  -0.3765
Total (uncentered) SS   =  2.692990899                Uncentered R2 =   0.9348
Residual SS             =  .1754636075                Root MSE      =   .04805

------------------------------------------------------------------------------
             |               Robust
water_poll~n |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |  -.0728056   .0468756    -1.55   0.120      -.16468    .0190689
     lngdp99 |  -.0222537   .0080196    -2.77   0.006    -.0379718   -.0065356
       _cons |   .5250096   .1656218     3.17   0.002     .2003968    .8496223
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):              5.400
                                                   Chi-sq(1) P-val =    0.0201
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):                4.913
                         (Kleibergen-Paap rk Wald F statistic):          5.020
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         entry
Included instruments: lngdp99
Excluded instruments: lnpop99
------------------------------------------------------------------------------

. ivreg2 unofficial_economy (entry=lnpop99), r first 

First-stage regressions
-----------------------

First-stage regression of entry:

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       72
                                                      F(  1,    70) =     6.42
                                                      Prob > F      =   0.0135
Total (centered) SS     =  19.21585364                Centered R2   =   0.0750
Total (uncentered) SS   =  373.1965579                Uncentered R2 =   0.9524
Residual SS             =  17.77398681                Root MSE      =    .5039

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lnpop99 |   .1049884    .041429     2.53   0.014     .0223608     .187616
       _cons |   .4653191   .6940581     0.67   0.505    -.9189362    1.849574
------------------------------------------------------------------------------
Included instruments: lnpop99
------------------------------------------------------------------------------
F test of excluded instruments:
  F(  1,    70) =     6.42
  Prob > F      =   0.0135
Angrist-Pischke multivariate F test of excluded instruments:
  F(  1,    70) =     6.42
  Prob > F      =   0.0135



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,    70)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    70)
entry        |       6.42    0.0135 |        6.61   0.0102 |        6.42

NB: first-stage test statistics heteroskedasticity-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=6.59     P-val=0.0103

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                       5.68
Kleibergen-Paap Wald rk F statistic                                 6.42

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,70)=        0.55     P-val=0.4615
Anderson-Rubin Wald test           Chi-sq(1)=      0.56     P-val=0.4526
Stock-Wright LM S statistic        Chi-sq(1)=      0.58     P-val=0.4451

NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity-robust

Number of observations               N  =         72
Number of regressors                 K  =          2
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          2
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       72
                                                      F(  1,    70) =     0.71
                                                      Prob > F      =   0.4039
Total (centered) SS     =   16714.5083                Centered R2   =   0.2050
Total (uncentered) SS   =  77529.24278                Uncentered R2 =   0.8286
Residual SS             =  13287.86526                Root MSE      =    13.59

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   8.581471   10.07569     0.85   0.394    -11.16652    28.32946
       _cons |   10.03519   22.14182     0.45   0.650    -33.36198    53.43236
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):              6.586
                                                   Chi-sq(1) P-val =    0.0103
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):                5.679
                         (Kleibergen-Paap rk Wald F statistic):          6.422
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         entry
Excluded instruments: lnpop99
------------------------------------------------------------------------------

. ivreg2 unofficial_economy lngdp99 (entry=lnpop99), r first 

First-stage regressions
-----------------------

First-stage regression of entry:

OLS estimation
--------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       72
                                                      F(  2,    69) =    12.80
                                                      Prob > F      =   0.0000
Total (centered) SS     =  19.21585364                Centered R2   =   0.2826
Total (uncentered) SS   =  373.1965579                Uncentered R2 =   0.9631
Residual SS             =   13.7845825                Root MSE      =     .447

------------------------------------------------------------------------------
             |               Robust
       entry |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     lngdp99 |  -.1543619   .0374515    -4.12   0.000    -.2290755   -.0796482
     lnpop99 |   .0840105   .0426799     1.97   0.053    -.0011336    .1691546
       _cons |    2.08557   .8221728     2.54   0.013     .4453797    3.725759
------------------------------------------------------------------------------
Included instruments: lngdp99 lnpop99
------------------------------------------------------------------------------
F test of excluded instruments:
  F(  1,    69) =     3.87
  Prob > F      =   0.0530
Angrist-Pischke multivariate F test of excluded instruments:
  F(  1,    69) =     3.87
  Prob > F      =   0.0530



Summary results for first-stage regressions
-------------------------------------------

                                           (Underid)            (Weak id)
Variable     | F(  1,    69)  P-val | AP Chi-sq(  1) P-val | AP F(  1,    69)
entry        |       3.87    0.0530 |        4.04   0.0444 |        3.87

NB: first-stage test statistics heteroskedasticity-robust

Stock-Yogo weak ID test critical values for single endogenous regressor:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Underidentification test
Ho: matrix of reduced form coefficients has rank=K1-1 (underidentified)
Ha: matrix has rank=K1 (identified)
Kleibergen-Paap rk LM statistic          Chi-sq(1)=4.20     P-val=0.0403

Weak identification test
Ho: equation is weakly identified
Cragg-Donald Wald F statistic                                       4.56
Kleibergen-Paap Wald rk F statistic                                 3.87

Stock-Yogo weak ID test critical values for K1=1 and L1=1:
                                   10% maximal IV size             16.38
                                   15% maximal IV size              8.96
                                   20% maximal IV size              6.66
                                   25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.

Weak-instrument-robust inference
Tests of joint significance of endogenous regressors B1 in main equation
Ho: B1=0 and orthogonality conditions are valid
Anderson-Rubin Wald test           F(1,69)=        0.01     P-val=0.9406
Anderson-Rubin Wald test           Chi-sq(1)=      0.01     P-val=0.9391
Stock-Wright LM S statistic        Chi-sq(1)=      0.01     P-val=0.9393

NB: Underidentification, weak identification and weak-identification-robust
    test statistics heteroskedasticity-robust

Number of observations               N  =         72
Number of regressors                 K  =          3
Number of endogenous regressors      K1 =          1
Number of instruments                L  =          3
Number of excluded instruments       L1 =          1

IV (2SLS) estimation
--------------------

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

                                                      Number of obs =       72
                                                      F(  2,    69) =    31.00
                                                      Prob > F      =   0.0000
Total (centered) SS     =   16714.5083                Centered R2   =   0.5197
Total (uncentered) SS   =  77529.24278                Uncentered R2 =   0.8965
Residual SS             =   8027.53462                Root MSE      =    10.56

------------------------------------------------------------------------------
             |               Robust
unofficial~y |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       entry |   -.973564   13.01135    -0.07   0.940    -26.47533    24.52821
     lngdp99 |  -7.381608   2.377749    -3.10   0.002    -12.04191   -2.721306
       _cons |   91.96195   47.78218     1.92   0.054    -1.689395    185.6133
------------------------------------------------------------------------------
Underidentification test (Kleibergen-Paap rk LM statistic):              4.205
                                                   Chi-sq(1) P-val =    0.0403
------------------------------------------------------------------------------
Weak identification test (Cragg-Donald Wald F statistic):                4.556
                         (Kleibergen-Paap rk Wald F statistic):          3.875
Stock-Yogo weak ID test critical values: 10% maximal IV size             16.38
                                         15% maximal IV size              8.96
                                         20% maximal IV size              6.66
                                         25% maximal IV size              5.53
Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
------------------------------------------------------------------------------
Hansen J statistic (overidentification test of all instruments):         0.000
                                                 (equation exactly identified)
------------------------------------------------------------------------------
Instrumented:         entry
Included instruments: lngdp99
Excluded instruments: lnpop99
------------------------------------------------------------------------------

. 
. 
. ****** FIGURE 3 ********
. qui reg unofficial_economy trust

. predict resshd, r
(169 missing values generated)

. qui reg water_pollution trust

. predict reswtr, r
(170 missing values generated)

. qui reg entry trust

. predict resprocs, r
(168 missing values generated)

. 
. twoway (scatter unofficial_economy entry) (lfit unofficial_economy entry), ytitle(Shadow Economy) ytitle(, margin(med
> ium)) xtitle(Ln Number of Procedures) xtitle(, margin(medium)) legend(off) scheme(s1color)

. graph copy shd, replace

. twoway (scatter water_pollution entry) (lfit water_pollution entry), ytitle(Water Pollution) ytitle(, margin(medium))
>  xtitle(Ln Number of Procedures) xtitle(, margin(medium)) legend(off) scheme(s1color)

. graph copy wtr, replace

. twoway (scatter resshd resprocs) (lfit resshd resprocs), ytitle("Shadow Economy | TRUST") ytitle(, margin(medium)) xt
> itle("Ln Number of Procedures | TRUST") xtitle(, margin(medium)) legend(off) scheme(s1color)

. graph copy shdres, replace

. twoway (scatter reswtr resprocs) (lfit reswtr resprocs), ytitle("Water Pollution | TRUST") ytitle(, margin(medium)) x
> title("Ln Number of Procedures | TRUST") xtitle(, margin(medium)) legend(off) scheme(s1color)

. graph copy wtrres, replace

. graph combine shd wtr shdres wtrres

. graph save figurebias, replace 
(file figurebias.gph saved)

. 
end of do-file

